共查询到18条相似文献,搜索用时 156 毫秒
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一种快速多人脸跟踪算法 总被引:1,自引:1,他引:0
提出一个基于肤色的快速多人脸跟踪算法.利用多个CAMShift跟踪器实现多人脸跟踪,提出最优排序法和目标消除法解决多人脸跟踪过程中目标发生粘连重叠的问题;引入多辅助信息和表决制解决了相邻两帧中人脸的对应问题.为进一步提高整个算法的跟踪速度和鲁棒性,引入卡尔曼滤波器对目标进行预测.实验结果表明,该算法可实时稳健地实现多人脸跟踪. 相似文献
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实现的人脸检测跟踪与特征点定位系统,基于VC++6.0开发平台,使用opencv作为开发工具,有效缩短了系统的开发时间。首先,本系统采用adaboost算法进行人脸检测,通过合理的特征模板的选择实现了人脸的实时检测;其次,人脸跟踪模块选用camshift算法,利用人脸检测模块生成的人脸坐标传递给跟踪模块,实现人脸的自动实时跟踪,同时建立多个camshift跟踪器对多人脸进行跟踪,并有效地解决了人脸遮挡的问题;最后,通过ASM(active shapemodel)算法实现了实时人脸特征点定位。实验结果表明该系统实现的人脸实时检测跟踪及特征点定位,效果明显,可以作为表情分析和情感计算、视频人脸识别开发的基础。 相似文献
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基于多特征Mean Shift的人脸跟踪算法 总被引:3,自引:1,他引:2
该文把局部三值模式(Local Ternary Patterns, LTP)纹理特征引入Mean Shift跟踪算法,提出了基于多特征的Mean Shift人脸跟踪算法以解决Mean shift跟踪算法的鲁棒性问题。通过对LTP纹理特征的分析、研究,提出了一个LTP关键纹理模型,既增强了目标的关键纹理信息,又简化了LTP纹理模型。在此基础上,提出一种基于LTP关键纹理特征和肤色特征的Mean Shift人脸跟踪算法,有效地解决了Mean Shift算法的鲁棒性问题。为进一步提高对快速运动目标的跟踪速度和跟踪性能,该文引入了卡尔曼滤波器对目标进行预测。实验结果表明,该文的算法在目标定位的准确性和跟踪性能上比Mean Shift算法均有明显的提高。 相似文献
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本文提出了一种在救援机器人中实现人脸检测、定位和跟踪的可行方案。首先通过摄像头将救援机器人周围的场景转化成数字图像,进行预处理后,使之成为易于检测和定位的图像,然后运用图像分割技术找到感兴趣的目标并进行定位,最后使用CamShift算法跟踪运动的人脸并驱动电机转动。 相似文献
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Nikolaos Katsarakis Aristodemos Pnevmatikakis Zheng-Hua Tan Ramjee Prasad 《Wireless Personal Communications》2014,78(3):1789-1810
Visual face tracking is an important building block for all intelligent living and working spaces, as it is able to locate persons without any human intervention or the need for the users to carry sensors on themselves. In this paper we present a novel face tracking system built on a particle filtering framework that facilitates the use of non-linear visual measurements on the facial area. We concentrate on three different such non-linear visual measurement cues, namely object detection, foreground segmentation and colour matching. We derive robust measurement likelihoods under a unified representation scheme and fuse them into our face tracking algorithm. This algorithm is complemented with optimum selection of the particle filter’s object model and a target handling scheme. The resulting face tracking system is extensively evaluated and compared to baseline ones. 相似文献
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《Signal Processing: Image Communication》2002,17(2):145-164
Automatic semantic video object extraction is an important step for providing content-based video coding, indexing and retrieval. However, it is very difficult to design a generic semantic video object extraction technique, which can provide variant semantic video objects by using the same function. Since the presence and absence of persons in an image sequence provide important clues about video content, automatic face detection and human being generation are very attractive for content-based video database applications. For this reason, we propose a novel face detection and semantic human object generation algorithm. The homogeneous image regions with accurate boundaries are first obtained by integrating the results of color edge detection and region growing procedures. The human faces are detected from these homogeneous image regions by using skin color segmentation and facial filters. These detected faces are then used as object seed for semantic human object generation. The correspondences of the detected faces and semantic human objects along time axis are further exploited by a contour-based temporal tracking procedure. 相似文献
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Joint object tracking and pose estimation is an important issue in Augmented Reality (AR), interactive systems, and robotic systems. Many studies are based on object detection methods that only focus on the reliability of the features. Other methods combine object detection with frame-by-frame tracking using the temporal redundancy in the video. However, in some mixed methods, the interval between consecutive detection frames is usually too short to take the full advantage of the frame-by-frame tracking, or there is no appropriate switching mechanism between detection and tracking. In this paper, an iterative optimization tracking method is proposed to alleviate the deviations of the tracking points and prolong the interval, and thus speed up the pose estimation process. Moreover, an adaptive detection interval algorithm is developed, which can make the switch between detection and frame-by-frame tracking automatically according to the quality of frames so as to improve the accuracy in a tough tracking environment. Experimental results on the benchmark dataset manifest that the proposed algorithms, as an independent part, can be combined with some inter-frame tracking methods for optimization. 相似文献
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随着航天科技的不断发展,计算机视觉算法在卫星上的应用方兴未艾,为了实现更多的功能需求和应对可能的威胁,视觉目标跟踪作为其中基础但具有挑战性的任务更是至关重要。然而,目前已有的目标跟踪算法大多数算法只限于对图像序列进行跟踪。另一方面,受到硬件条件制约,很多优秀的算法因为复杂度较高很少被应用到星载嵌入式系统中。这些目标跟踪算法运行时,通常需要人为地给出目标的边界框。为了自动得到边界框,需要目标检测算法对输入图像进行运动目标检测。本文提出了一种基于显著性检测和相关滤波的单目标检测与跟踪一体化算法,并与嵌入式系统相结合,在搭载的TMS320C6678芯片上达到了2 048 pixel×2 048 pixel分辨率下24 fps的帧率。具体地,检测算法负责对图像进行预处理并获得边界框,然后目标跟踪算法给出目标在后续帧中的位置。为了验证算法在实际跟踪中的有效性,本研究搭建了一个由相机、DSP和云台组成的光学平台并进行了实验验证。在该系统中,DSP自动完成检测、跟踪、驱动云台和再检测任务,达到了很好的检测跟踪效果。 相似文献
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提出了一种基于区域特征的快速人脸检测算法.采用瞬时差分和背景差分获取并跟踪运动目标.消除了运动目标引起的背景模型更新误差.在检测到的运动目标区域内.通过基于区域特征的马赛克三分图模型检测人脸区域,并利用频率直方图方法合并所检测区域,最终获得人脸位置.实验结果表明,平均检测时间为30ms/帧,检测准确率可达95.7%,算法复杂度低、检测效果好,适合各类视频图像的人脸实时检测. 相似文献
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Wenlong Zheng Suchendra M. Bhandarkar 《Journal of Visual Communication and Image Representation》2009,20(1):9-27
A novel algorithm, termed a Boosted Adaptive Particle Filter (BAPF), for integrated face detection and face tracking is proposed. The proposed algorithm is based on the synthesis of an adaptive particle filtering algorithm and the AdaBoost face detection algorithm. An Adaptive Particle Filter (APF), based on a new sampling technique, is proposed. The APF is shown to yield more accurate estimates of the proposal distribution and the posterior distribution than the standard Particle Filter thus enabling more accurate tracking in video sequences. In the proposed BAPF algorithm, the AdaBoost algorithm is used to detect faces in input image frames, whereas the APF algorithm is designed to track faces in video sequences. The proposed BAPF algorithm is employed for face detection, face verification, and face tracking in video sequences. Experimental results show that the proposed BAPF algorithm provides a means for robust face detection and accurate face tracking under various tracking scenarios. 相似文献